The Digital Twin Paradigm for Smarter Systems and Environments: The Industry Use Cases: Advances in Computers, cartea 117
Pethuru Raj, Preetha Evangeline Daviden Limba Engleză Hardback – 27 ian 2020
- Provides in-depth descriptions of digital transformation technologies and tools
- Covers various research accomplishments in this flourishing field of relevance
- Includes many detailed industry use cases with all the right information
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Specificații
ISBN-13: 9780128187562
ISBN-10: 0128187565
Pagini: 384
Dimensiuni: 152 x 229 x 28 mm
Greutate: 0.69 kg
Editura: ELSEVIER SCIENCE
Seria Advances in Computers
ISBN-10: 0128187565
Pagini: 384
Dimensiuni: 152 x 229 x 28 mm
Greutate: 0.69 kg
Editura: ELSEVIER SCIENCE
Seria Advances in Computers
Public țintă
Data scientists, artificial intelligence (AI) researchers, big data analytics (BDA) architects, IoT experts, IT professionalsCuprins
1. Stepping into the digitally instrumented and interconnected era Pethuru Raj and Jenn-Wei Lin 2. Digital twin technology for "smart manufacturing" Preetha David and Anandhakumar 3. The fog computing/edge computing to leverage digital twin J. Pushpa and Kalayani 4. The industry use cases for the Digital Twin idea Peter Augustine 5. Digital twin: Empowering edge devices to be intelligent Vidya Hungud and Senthil Kumar Arunachalam 6. The industrial internet of things (IIoT) Sathyan Munirathinam 7. The growing role of integrated and insightful big and real-time data analytics platforms Indrakumari Ranganathan, Poongodi Thangamuthu, Suresh Palanimuthu and Balamurugan Balusamy 8. Air pollution control model using machine learning and IoT techniques Chetan Shetty, B.J. Sowmya, S. Seema and K.G. Srinivasa 9. The human body: A digital twin of the cyber physical systems Janet Barnabas and Pethuru Raj 10. Impact of cloud security in digital twin Susila Nagarajan, Sruthi Anand and Usha Sakthivel 11. Digital twin in consumer choice modeling D. Sudaroli Vijayakumar 12. Digital twin: The industry use cases Pethuru Raj and Chellammal Surianarayanan 13. Machine learning and deep learning algorithms on the Industrial Internet of Things (IIOT) P. Ambika 14. Energy-efficient edge based real-time healthcare support system S. Abirami and P. Chitra